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Land
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Harnessing the Power of Land Mapping Data for Effective Land...
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Harnessing the Power of Land Mapping Data for Effective Land Policy Development

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land Innovations – Data and Machine Learning".

Deadline for manuscript submissions: closed (31 December 2025) | Viewed by 6607

Special Issue Editors

Dr. Xiao Huang

E-Mail Website
Guest Editor
Department of Environmental Sciences, Emory University, Atlanta, GA, USA
Interests: GeoAI and deep learning; disaster remote sensing; human–environment interaction; computational social sciences
Special Issues, Collections and Topics in MDPI journals
Dr. Zehua Zhang

E-Mail Website
Guest Editor
School of Design and the Built Environment, Curtin University, Perth 6102, Australia
Interests: spatial statistics; spatial data science; GIS; spatial planning
Dr. Cheolhee Yoo

E-Mail Website
Guest Editor
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Interests: urban environment; urban sustainability; urban climate; remote sensing; GIS; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land mapping datasets have become one of the most critical sources of spatial information supporting land use policy and decision-making for achieving sustainable goals both socioeconomically and environmentally. Practical applications of land mapping data include environmental monitoring, urbanization assessment, spatial dynamics evaluation, and so on. Advances in remote sensing, crowdsourcing and citizen science, spatial statistics, and GIS greatly enhance the planning insights and diverse functionalities of land mapping.

The goal of this Special Issue is to collect papers (original research articles and review papers) to give insights on the advances and applications of land mapping techniques and associated data analysis and management works in assisting the achievement of sustainable development targets and other socioeconomic or environmental goals. Research works on land use policy and management based on land mapping datasets are also welcome to be submitted to this Special Issue.

This Special Issue will welcome manuscripts that link the following themes:

  • Advances in land mapping and remote sensing techniques;
  • Research and reviews on land policy or land use management using land mapping data;
  • Research applications of land mapping to achieve sustainable development goals;
  • Geospatial data analysis and management on land mapping data;
  • Other works that are highly associated with land mapping and land use policy.

We look forward to receiving your original research articles and reviews.

Dr. Xiao Huang
Dr. Zehua Zhang
Dr. Cheolhee Yoo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • land mapping
  • land use policy and management
  • land use and land cover (LULC) monitoring
  • remote sensing
  • spatial data
  • sustainable development
  • environmental monitoring

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

27 pages, 11861 KB  
Article
Spatiotemporal Evolution and Scenario Simulation of Landscape Ecological Risk in Hilly–Gully Regions: A Case Study of Zichang City
by Zhongqian Zhang, Huanli Pan, Jing Gan, Shuangqing Sheng and Guoyang Lu
Land 2025, 14(12), 2358; https://doi.org/10.3390/land14122358 - 2 Dec 2025
Cited by 2 | Viewed by 660
Abstract
The evolution of landscape ecological risk in ecologically fragile areas constitutes a critical foundation for optimizing territorial spatial planning and ensuring ecological security. This study takes Zichang City as the research object and integrates the dynamic analysis of land use, landscape ecological risk [...] Read more.
The evolution of landscape ecological risk in ecologically fragile areas constitutes a critical foundation for optimizing territorial spatial planning and ensuring ecological security. This study takes Zichang City as the research object and integrates the dynamic analysis of land use, landscape ecological risk assessment, and spatial simulation into a single framework. By analyzing the laws of land use change in Zichang City from 1980 to 2020, the CLUE-S model was used to predict land use change and ecological risks under multiple scenarios in 2035. Statistical and spatial analysis methods were comprehensively applied to verify the robustness and spatial differentiation characteristics of the risk assessment. Key findings indicate the following: (1) From 1980 to 2020, forest land, water bodies, and construction land in Zichang City continued to increase, while cultivated land and grassland tended to decrease. Multi-scenario simulations showed that under the business-as-usual scenario, grassland and forest land expanded; under the economic development scenario, urban land increased significantly; under the ecological protection scenario, grassland grew substantially, while cultivated land contracted noticeably. (2) The overall LERI from 1980 to 2020 first declined and then slightly rebounded, reflecting an “initial improvement followed by fluctuation” in ecological security, with a spatial pattern of “high in the central area, low in the periphery.” By 2035, high-risk levels remain predominant across scenarios, although the proportion of high-risk areas is limited. Monte Carlo simulation confirmed the robustness of the assessment (mean CV = 0.038). (3) Spatially, from 2020 to 2035, the clustering characteristics of LERI varied among scenarios; however, high–high and low–low clustering patterns remained predominant, indicating that spatial aggregation of ecological risk is relatively stable across scenarios. This study demonstrates that integrating landscape ecological risk assessment with land use scenario modeling provides robust scientific support for optimizing spatial planning and ecological security in ecologically fragile regions. The proposed framework offers methodological guidance and practical reference for identifying key risk areas and designing differentiated land use and risk management strategies in similar hilly–gully landscapes. Full article
(This article belongs to the Special Issue Harnessing the Power of Land Mapping Data for Effective Land Policy Development)
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26 pages, 9382 KB  
Article
Benefits and Trade-Offs from Land Use and Land Cover Changes Under Different Scenarios in the Coastal Delta of Vietnam
by Nguyen Thi Hong Diep, Nguyen Trong Nguyen, Phan Kieu Diem and Can Trong Nguyen
Land 2025, 14(5), 1063; https://doi.org/10.3390/land14051063 - 13 May 2025
Cited by 3 | Viewed by 3566
Abstract
Land use and land cover (LULC) in coastal areas is critical in shaping the ecological systems, regional economy, and livelihood of indigenous communities. This study analyzes LULC changes (LULCC) in Soc Trang Province, Vietnam Mekong Delta, from 2010 to 2020 and simulates future [...] Read more.
Land use and land cover (LULC) in coastal areas is critical in shaping the ecological systems, regional economy, and livelihood of indigenous communities. This study analyzes LULC changes (LULCC) in Soc Trang Province, Vietnam Mekong Delta, from 2010 to 2020 and simulates future LULC for 2030 under four scenarios: natural growth (business as usual, BAU), climate change challenges, profit optimization, and adaptation strategies. Satellite-based LULC maps and geospatial datasets were integrated into a LULC simulation model based on a Markov Chain and Cellular Automata to predict LULC in 2030 under disparate scenarios. Simultaneously, this study also estimates economic values and ecosystem service values as proxies to evaluate benefits and trade-offs between the scenarios. The research findings reveal that the critical LULCC observed during 2010–2020 are transitions from triple rice crops to double rice crops, rice–shrimp to brackish aquaculture, and expansion of perennial plantations. These transitional trends will persist at a modest rate under the BAU scenario in 2030. The climate change challenge scenario will intervene up to 24.2% of the total area, with double rice crops reaching the most extensive area compared to other scenarios, about 106,047 ha. The profit optimization scenario will affect 16.03% of the total area, focusing on aquaculture expansion to the maximum shared proportion of 34% (approximately 57,000 ha). Adaptive solutions will emphasize reducing triple rice crops while expanding double rice crops and reviving rice–shrimp to different extents depending on development pathways. Economic evaluations show a growth trend across scenarios, with maximum returns under profit optimization. Yet, ecosystem service values notably highlight ecological trade-offs, raising concerns about balancing economic benefits and ecological trade-offs in land use planning. The research findings recommend a comprehensive and multitarget approach to land use planning that integrates ecosystem services into initial assessments to balance benefits and trade-offs in coastal areas commonly affected by LULCC. By adopting well-informed and strategic land use plans that minimize ecological and social impacts, local sustainability and resilience to climate change can be significantly enhanced. Full article
(This article belongs to the Special Issue Harnessing the Power of Land Mapping Data for Effective Land Policy Development)
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21 pages, 6115 KB  
Article
Spatiotemporal Landslide Monitoring in Complex Environments Using Radiative Transfer Model and SBAS-InSAR Technology
by Bing Wang, Li He, Zhengwei He, Yongze Song, Rui Qu, Jiao Hu, Zhifei Wang and Zehua Zhang
Land 2025, 14(5), 956; https://doi.org/10.3390/land14050956 - 28 Apr 2025
Viewed by 1463
Abstract
Landslides are among the most frequent geological hazards, often resulting in casualties and economic losses, particularly in alpine valley areas characterized by complex topography and dense vegetation. Landslides in these regions are distinguished by their high altitude, concealment, and sudden onset, which render [...] Read more.
Landslides are among the most frequent geological hazards, often resulting in casualties and economic losses, particularly in alpine valley areas characterized by complex topography and dense vegetation. Landslides in these regions are distinguished by their high altitude, concealment, and sudden onset, which render traditional monitoring methods inefficient. This study proposes a landslide monitoring method for complex environments that leverages multi-source remote sensing data, incorporating the radiative transfer model and Small Baseline Subset-Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology. The proposed method was implemented to monitor the instability of the Baige landslide in Tibet, China. The results show that the vegetation Canopy Water Content (CWC) estimated using the radiative transfer model indirectly reflects landslide susceptibility. Specifically, excessive soil moisture from rainfall reduces oxygen in plant roots, affecting growth and lowering canopy water content. The region with lower Canopy Water Content (CWC < 0.04) exhibited an increasing trend in the number of pixels, rising from 271 to 549 before the landslide event, indicating poorer vegetation conditions in the area. Additionally, the SBAS-InSAR technique was utilized to extract surface displacement, achieving a maximum displacement of 112 mm during the monitoring period. Ultimately, the spatial changes of the two monitoring signals exhibited a high consistency. This study enhances the reliability of landslide displacement monitoring in complex environments and provides substantial scientific support for future large-scale monitoring efforts. Full article
(This article belongs to the Special Issue Harnessing the Power of Land Mapping Data for Effective Land Policy Development)
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